When Gaussian process meets big data: A review of scalable GPs

H Liu, YS Ong, X Shen, J Cai - IEEE transactions on neural …, 2020 - ieeexplore.ieee.org
The vast quantity of information brought by big data as well as the evolving computer
hardware encourages success stories in the machine learning community. In the …

Mixture of experts: a literature survey

S Masoudnia, R Ebrahimpour - Artificial Intelligence Review, 2014 - Springer
Mixture of experts (ME) is one of the most popular and interesting combining methods, which
has great potential to improve performance in machine learning. ME is established based on …

Scaling vision with sparse mixture of experts

C Riquelme, J Puigcerver, B Mustafa… - Advances in …, 2021 - proceedings.neurips.cc
Abstract Sparsely-gated Mixture of Experts networks (MoEs) have demonstrated excellent
scalability in Natural Language Processing. In Computer Vision, however, almost all …

[BOOK][B] The EM algorithm and extensions

GJ McLachlan, T Krishnan - 2008 - books.google.com
The only single-source——now completely updated and revised——to offer a unified
treatment of the theory, methodology, and applications of the EM algorithm Complete with …

[BOOK][B] Statistical pattern recognition

AR Webb - 2003 - books.google.com
Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …

EEG signal classification using wavelet feature extraction and a mixture of expert model

A Subasi - Expert Systems with Applications, 2007 - Elsevier
Mixture of experts (ME) is modular neural network architecture for supervised learning. A
double-loop Expectation-Maximization (EM) algorithm has been introduced to the ME …

M³vit: Mixture-of-experts vision transformer for efficient multi-task learning with model-accelerator co-design

Z Fan, R Sarkar, Z Jiang, T Chen… - Advances in …, 2022 - proceedings.neurips.cc
Multi-task learning (MTL) encapsulates multiple learned tasks in a single model and often
lets those tasks learn better jointly. Multi-tasking models have become successful and often …

Adamv-moe: Adaptive multi-task vision mixture-of-experts

T Chen, X Chen, X Du, A Rashwan… - Proceedings of the …, 2023 - openaccess.thecvf.com
Abstract Sparsely activated Mixture-of-Experts (MoE) is becoming a promising paradigm for
multi-task learning (MTL). Instead of compressing multiple tasks' knowledge into a single …

Twenty years of mixture of experts

SE Yuksel, JN Wilson, PD Gader - IEEE transactions on neural …, 2012 - ieeexplore.ieee.org
In this paper, we provide a comprehensive survey of the mixture of experts (ME). We discuss
the fundamental models for regression and classification and also their training with the …

Scaling vision-language models with sparse mixture of experts

S Shen, Z Yao, C Li, T Darrell, K Keutzer… - arxiv preprint arxiv …, 2023 - arxiv.org
The field of natural language processing (NLP) has made significant strides in recent years,
particularly in the development of large-scale vision-language models (VLMs). These …